Financial data is often analyzed to gain information of interest. For example, assets in a portfolio are often analyzed to minimize risk in the portfolio and optimize return. As another example, pricing a bond may involve complex data analysis that takes into consideration a number of factors (e.g., yield, maturity date, risk, etc.) associated with the bond. Financial analysis programs are often used to perform these tasks. However, such financial programs are often inefficient and suffer from interoperability issues between various tools or functions.
For example, considerable data input is often required in order for a user to perform a particular function that may be repeated many times. Such data input is typically time consuming and inefficient. In addition, each particular function may have a different input mechanism associated with performing the desired calculation. This may make it difficult for the user to interact with the program to perform multiple calculations. Still further, different tools or functions within a program often perform similar processing with respect to analyzing financial data. However, due to interoperability issues, one tool or function cannot typically use a structure or function associated with another tool/function.